analyzing-network-traffic-with-wireshark
Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns, diagnose protocol issues, extract artifacts, and support incident response investigations on authorized network segments.
Best use case
analyzing-network-traffic-with-wireshark is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns, diagnose protocol issues, extract artifacts, and support incident response investigations on authorized network segments.
Teams using analyzing-network-traffic-with-wireshark should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/analyzing-network-traffic-with-wireshark/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How analyzing-network-traffic-with-wireshark Compares
| Feature / Agent | analyzing-network-traffic-with-wireshark | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns, diagnose protocol issues, extract artifacts, and support incident response investigations on authorized network segments.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Analyzing Network Traffic with Wireshark
## When to Use
- Investigating suspected network intrusions by examining packet-level evidence of command-and-control traffic, data exfiltration, or lateral movement
- Diagnosing network performance issues such as retransmissions, fragmentation, or DNS resolution failures
- Analyzing malware communication patterns by capturing traffic from sandboxed or isolated hosts
- Validating firewall and IDS rules by confirming what traffic is actually traversing network segments
- Extracting files, credentials, or indicators of compromise from captured network sessions
**Do not use** to capture traffic on networks without authorization, to intercept private communications without legal authority, or as a substitute for full-featured SIEM platforms in production monitoring.
## Prerequisites
- Wireshark 4.0+ and tshark command-line utility installed
- Root/sudo privileges or membership in the `wireshark` group for live packet capture
- Network interface access (physical NIC, span port, or network tap) to the monitored segment
- Sufficient disk space for packet capture files (estimate 1 GB per minute on busy gigabit links)
- Familiarity with TCP/IP protocols, HTTP, DNS, TLS, and SMB at the packet level
## Workflow
### Step 1: Configure Capture Environment
Set up the capture interface and filters to target relevant traffic:
```bash
# List available interfaces
tshark -D
# Start capture on eth0 with a capture filter to limit scope
tshark -i eth0 -f "host 10.10.5.23 and (port 80 or port 443 or port 445)" -w /tmp/capture.pcapng
# Capture with ring buffer to manage disk usage (10 files, 100MB each)
tshark -i eth0 -b filesize:102400 -b files:10 -w /tmp/rolling_capture.pcapng
# Capture on multiple interfaces simultaneously
tshark -i eth0 -i eth1 -w /tmp/multi_interface.pcapng
```
For Wireshark GUI, set capture filter in the Capture Options dialog before starting.
### Step 2: Apply Display Filters for Targeted Analysis
```bash
# Filter HTTP traffic containing suspicious user agents
tshark -r capture.pcapng -Y "http.user_agent contains \"curl\" or http.user_agent contains \"Wget\""
# Find DNS queries to suspicious TLDs
tshark -r capture.pcapng -Y "dns.qry.name contains \".xyz\" or dns.qry.name contains \".top\" or dns.qry.name contains \".tk\""
# Identify TCP retransmissions indicating network issues
tshark -r capture.pcapng -Y "tcp.analysis.retransmission"
# Filter SMB traffic for lateral movement detection
tshark -r capture.pcapng -Y "smb2.cmd == 5 or smb2.cmd == 3" -T fields -e ip.src -e ip.dst -e smb2.filename
# Find cleartext credential transmission
tshark -r capture.pcapng -Y "ftp.request.command == \"PASS\" or http.authbasic"
# Detect beaconing patterns (regular interval connections)
tshark -r capture.pcapng -Y "ip.dst == 203.0.113.50" -T fields -e frame.time_relative -e ip.src -e tcp.dstport
```
### Step 3: Protocol-Specific Deep Analysis
```bash
# Follow a TCP stream to reconstruct a conversation
tshark -r capture.pcapng -q -z follow,tcp,ascii,0
# Analyze HTTP request/response pairs
tshark -r capture.pcapng -Y "http" -T fields -e frame.time -e ip.src -e ip.dst -e http.request.method -e http.request.uri -e http.response.code
# Extract DNS query/response statistics
tshark -r capture.pcapng -q -z dns,tree
# Analyze TLS handshakes for weak cipher suites
tshark -r capture.pcapng -Y "tls.handshake.type == 2" -T fields -e ip.src -e ip.dst -e tls.handshake.ciphersuite
# SMB file access enumeration
tshark -r capture.pcapng -Y "smb2" -T fields -e frame.time -e ip.src -e ip.dst -e smb2.filename -e smb2.cmd
```
### Step 4: Extract Artifacts and IOCs
```bash
# Export HTTP objects (files transferred over HTTP)
tshark -r capture.pcapng --export-objects http,/tmp/http_objects/
# Export SMB objects (files transferred over SMB)
tshark -r capture.pcapng --export-objects smb,/tmp/smb_objects/
# Extract all unique destination IPs for threat intelligence lookup
tshark -r capture.pcapng -T fields -e ip.dst | sort -u > unique_dest_ips.txt
# Extract SSL/TLS certificate information
tshark -r capture.pcapng -Y "tls.handshake.type == 11" -T fields -e x509sat.uTF8String -e x509ce.dNSName
# Extract all URLs accessed
tshark -r capture.pcapng -Y "http.request" -T fields -e http.host -e http.request.uri | sort -u > urls.txt
# Hash extracted files for IOC matching
find /tmp/http_objects/ -type f -exec sha256sum {} \; > extracted_file_hashes.txt
```
### Step 5: Statistical Analysis and Anomaly Detection
```bash
# Protocol hierarchy statistics
tshark -r capture.pcapng -q -z io,phs
# Conversation statistics sorted by bytes
tshark -r capture.pcapng -q -z conv,tcp -z conv,udp
# Identify top talkers
tshark -r capture.pcapng -q -z endpoints,ip
# IO graph data (packets per second)
tshark -r capture.pcapng -q -z io,stat,1,"COUNT(frame) frame"
# Detect port scanning patterns
tshark -r capture.pcapng -Y "tcp.flags.syn == 1 and tcp.flags.ack == 0" -T fields -e ip.src -e tcp.dstport | sort | uniq -c | sort -rn | head -20
```
### Step 6: Generate Reports and Export Evidence
```bash
# Export filtered packets to a new PCAP for evidence preservation
tshark -r capture.pcapng -Y "ip.addr == 10.10.5.23 and tcp.port == 4444" -w evidence_c2_traffic.pcapng
# Generate packet summary in CSV format
tshark -r capture.pcapng -T fields -E header=y -E separator=, -e frame.number -e frame.time -e ip.src -e ip.dst -e ip.proto -e tcp.srcport -e tcp.dstport -e frame.len > traffic_summary.csv
# Create PDML (XML) output for programmatic analysis
tshark -r capture.pcapng -T pdml > capture_analysis.xml
# Calculate capture file hash for chain of custody
sha256sum capture.pcapng > capture_hash.txt
```
## Key Concepts
| Term | Definition |
|------|------------|
| **Capture Filter (BPF)** | Berkeley Packet Filter syntax applied at capture time to limit which packets are recorded, reducing file size and improving performance |
| **Display Filter** | Wireshark-specific filter syntax applied to already-captured packets for focused analysis without altering the capture file |
| **PCAPNG** | Next-generation packet capture format supporting multiple interfaces, name resolution, annotations, and metadata in a single file |
| **TCP Stream** | Reassembled sequence of TCP segments representing a complete bidirectional conversation between two endpoints |
| **Protocol Dissector** | Wireshark module that decodes a specific protocol's fields and structure, enabling deep inspection of packet contents |
| **IO Graph** | Time-series visualization of packet or byte rates over the capture duration, useful for identifying traffic spikes or beaconing |
## Tools & Systems
- **Wireshark 4.0+**: GUI-based packet analyzer with protocol dissectors for 3,000+ protocols, stream reassembly, and export capabilities
- **tshark**: Command-line version of Wireshark for headless capture, batch processing, and scripted analysis pipelines
- **tcpdump**: Lightweight packet capture tool for quick captures on remote systems without GUI dependencies
- **mergecap**: Wireshark utility for combining multiple capture files into a single PCAP for unified analysis
- **editcap**: Wireshark utility for splitting, filtering, and converting between capture file formats
## Common Scenarios
### Scenario: Investigating Suspected Data Exfiltration via DNS Tunneling
**Context**: The SOC team detected unusually high DNS query volumes from a workstation (10.10.3.45) to an external domain. The SIEM alert flagged DNS queries averaging 200 per minute compared to the baseline of 15. A packet capture was initiated from the network tap on the workstation's VLAN.
**Approach**:
1. Capture traffic from the workstation's subnet using `tshark -i eth2 -f "host 10.10.3.45 and port 53" -w dns_exfil_investigation.pcapng`
2. Analyze DNS query patterns: `tshark -r dns_exfil_investigation.pcapng -Y "dns.qry.name contains \"suspect-domain.xyz\"" -T fields -e frame.time -e dns.qry.name`
3. Examine subdomain labels for encoded data (long base64-like subdomains indicate tunneling): `tshark -r dns_exfil_investigation.pcapng -Y "dns.qry.type == 16" -T fields -e dns.qry.name -e dns.txt`
4. Calculate data volume by summing query name lengths to estimate exfiltration bandwidth
5. Extract unique query names and decode base64 subdomains to recover exfiltrated content
6. Export evidence packets to a separate PCAP and generate SHA-256 hash for chain of custody
**Pitfalls**:
- Capturing unfiltered traffic on a busy network and running out of disk space before collecting relevant data
- Using display filters instead of capture filters, resulting in massive files that are slow to process
- Overlooking encrypted DNS (DoH/DoT) traffic that bypasses traditional DNS capture on port 53
- Failing to establish packet capture hash and chain of custody documentation for forensic evidence
## Output Format
```
## Traffic Analysis Report
**Case ID**: IR-2024-0847
**Capture File**: dns_exfil_investigation.pcapng
**SHA-256**: a3f2b8c1d4e5f6a7b8c9d0e1f2a3b4c5d6e7f8a9b0c1d2e3f4a5b6c7d8e9f0a1
**Duration**: 2024-03-15 14:00:00 to 14:45:00 UTC
**Source Interface**: eth2 (VLAN 30 span port)
### Findings
**1. DNS Tunneling Confirmed**
- Source: 10.10.3.45
- Destination DNS: 8.8.8.8 (forwarded to ns1.suspect-domain.xyz)
- Query volume: 9,247 queries in 45 minutes (205/min vs 15/min baseline)
- Average subdomain label length: 63 characters (base64-encoded data)
- Estimated data exfiltrated: ~2.3 MB via TXT record responses
**2. Indicators of Compromise**
- Domain: suspect-domain.xyz (registered 3 days prior)
- Nameserver: ns1.suspect-domain.xyz (203.0.113.50)
- Query pattern: TXT record requests with base64-encoded subdomains
- Response pattern: TXT records containing base64-encoded payloads
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